3 citations · 3 across the 7 of their papers we have counts for
4 papers · 1 filter
Residual-Based Adaptive Kalman Filtering for Legged Robot State Estimation
Mihaela Popescu, Dennis Mronga, Shivesh Kumar +1
State estimation is a key component in model-based control of walking robots and, more broadly, applicable wherever hidden variables must be inferred. The Kalman filter is widely u…
Adaptive Model-Base Control of Quadrupeds via Online System Identification using Kalman Filter
Jonas Haack, Franek Stark, Shubham Vyas +2
Many real-world applications require legged robots to be able to carry variable payloads. Model-based controllers such as model predictive control (MPC) have become the de facto st…
Reinforcement Learning for Robust Athletic Intelligence: Lessons from the 2nd 'AI Olympics with RealAIGym' Competition
Felix Wiebe, Niccolò Turcato, Alberto Dalla Libera +17
In the field of robotics many different approaches ranging from classical planning over optimal control to reinforcement learning (RL) are developed and borrowed from other fields…
Model Predictive Parkour Control of a Monoped Hopper in Dynamically Changing Environments
Maximilian Albracht, Shivesh Kumar, Shubham Vyas +1
A great advantage of legged robots is their ability to operate on particularly difficult and obstructed terrain, which demands dynamic, robust, and precise movements. The study of…